(1) Field of the Invention
The present invention relates to a personal authentication system using fingerprint information suitable for authenticating a personal identification utilizing, e.g., a fingerprint pattern; to a registration-and-authentication method for the system; and to a determination method for the system.
(2) Description of the Related Art
Personal authentication systems using biological information, such as fingerprints, have recently been commercially available. The biological information (hereinafter called biometric information) utilizes, for example, a fingerprint, a palm print, a finger shape, a palm shape, voice, a retina, an iris, a face image, a dynamic signature, blood-vessel arrangements, or keystroke. The biometric information is superior in reliability to a password. Of biometric information, a fingerprint is used frequently.
In a personal authentication system using a fingerprint, a fingerprint is to be checked against all sample fingerprints by means of round-robin matching. For instance, the authentication system employs a matching method (matching technique) of so-called one-fingerprint-against-multiple-registered-fingerprints type (hereinafter simply called a “1-N fingerprint matching method”). Round-robin matching is a technique of checking a fingerprint against all the registered fingerprint data for matching purpose, in sequence from the top. If fingerprint data pertaining to a person of interest are coincidentally located at the head of the sequence, it is expected that matching processing can be terminated immediately without involvement of matching operation using a fingerprint pattern.
The round-robin matching technique verifies an individual without use of an ID (identification). Hence, according to the technique, matching requires a massive amount of computation until a person of interest is authenticated.
In order to avoid massive amounts of processing time, there have already been conceived various methods which shorten a matching time required for the 1-N matching method, by means of detecting the type of a fingerprint pattern and checking the fingerprint against fingerprints having patterns of the same type.
For example, Japanese Patent Application Laid-Open (Kokai) No. HEI 7-29003 (hereinafter called “Publicly-Known Publication 1”) describes a fingerprint matching system capable of shortening a matching time. In this system, characteristic data for matching purpose are extracted from fingerprint images of a plurality of fingerprints, and the thus-extracted data are registered in a filed fingerprint data storage section. Characteristic data for matching are extracted from a fingerprint image to be authenticated (hereinafter called a “search fingerprint”). The system determines, from among the filed fingerprints (hereinafter called “filed fingerprints”) registered in the filed fingerprint data storage section, a filed fingerprint whose characteristic data have the highest degree of similarity to the characteristic data extracted from the search fingerprint.
At the time of fingerprint matching, additional information appended to the data pertaining to the fingerprint to be authenticated is compared with additional information appended to the data pertaining to the registered fingerprints. Filed fingerprints whose additional information does not match the additional information about the fingerprint to be authenticated are eliminated from fingerprints to be matched, thereby shortening overall matching time.
According to the fingerprint authentication method utilizing a fingerprint pattern, if no match exists between registered fingerprint patterns for matching purpose and a fingerprint pattern to be authenticated, the person having the fingerprint to be authenticated is identified as being a different person. According to this method, when a fingerprint image is captured, the fingerprint may be determined to differ from a true fingerprint, depending on the angle at which a finger is placed on a fingerprint scanner (hereinafter often simply called a “scanner”) or the circumstances of sampling of a fingerprint, such as the position of a finger on the scanner (hereinafter called “fingerprint-sampling circumstances”). In this case, normal personal authentication cannot be effected, and the captured fingerprint is checked against only fingerprints whose patterns do not match that of the captured fingerprint. If no match is found between the fingerprint to be authenticated and a group of registered fingerprints for matching purposes whose finger patterns are similar to that of the fingerprint to be authenticated, the fingerprint to be authenticated is checked against all registered fingerprints for matching purpose whose patterns are different from that of the fingerprint to be authenticated. This method is not much different from mere round-robin matching.
In addition, various methods for determining a fingerprint pattern have already been put forward. Japanese Patent Application Laid-Open (Kokai) No. HEI 9-44666 (hereinafter called “Publicly-Known Publication 2”) describes a classification apparatus for classifying a skin pattern and a fingerprint pattern which tracks and classifies a skin pattern line such as a palm print or a fingerprint. The skin-pattern-line tracking apparatus described in Publicly-Known Publication 2 extracts characteristic points appearing in characteristic patterns. If characteristic lines are present around the characteristic points, the characteristic lines are tracked, thereby extracting a feature of the fingerprint pattern and determining the type of the fingerprint pattern.
FIG. 33 is an illustration for describing types of fingerprint patterns, showing five print patterns; namely, a plain arch pattern α, a tented arch pattern β, a right loop pattern γ, a left loop pattern δ, and a whorl pattern ε. In the classification shown in FIG. 33, the plain arch pattern α has no characteristic point appearing in a semi-circular area (hereinafter called a “core-type characteristic point”); each of the tented arch pattern β, the right loop pattern γ, and the left loop pattern δ has one core-type characteristic point; and the whorl pattern ε has two core-type characteristic points.
Characteristic points appearing in a delta area (hereinafter called “delta-type characteristic points”) are equal in number to the core-type characteristic points. A fingerprint image sometimes cannot be practically obtained over a sufficiently wide area. For this reason, automatic detection of a fingerprint produced by means of pressing a finger against a scanner is sometimes difficult. In this regard, Publicly-Known Publication 2 describes classification of fingerprints according to a core-type characteristic point.
In the category of the right loop pattern γ, the left loop pattern δ, and the tented arch pattern β, many similar patterns are difficult to classify between two categories; namely, the loop patterns γ and δ and the tented arch pattern β. At the time of drawing a distinction between these two types of patterns, care must be paid in determining whether or not a pattern includes a loop line. The right loop pattern γ and the left loop pattern δ include a loop line, whereas the tented arch pattern β consists of an arch line and does not include a loop line.
FIG. 34(a) is an illustration for describing a loop line. Each of ridge lines (curved lines constituting a pattern) a1-ar and bl-br shown in FIG. 34(a) has a horseshoe pattern. Ends of each of horseshoe-shaped ridge lines are oriented in one direction. Namely, ends of the two left loop lines a1-ar and bl-br are oriented in substantially a leftward direction, as shown in FIG. 34(a). Ends of two right loop lines [not shown in FIG. 34(a)] are oriented in substantially a rightward direction.
FIG. 34(b) is an illustration for describing a tented arch line. Each of ridge lines al-ar, bl-br, and cl-cr shown in FIG. 34(b) is separated into the right and left sides, as viewed from the tented portion of the arch pattern.
A ridge line is not always continuous and often shows discontinuities. In such a case, the discontinuities of the ridge line are complemented, as required, and the thus-complemented ridge line is tracked. The type of a fingerprint pattern including the ridge line is determined on the basis of whether or not ends of the thus-tracked ridge line satisfy the foregoing requirements. As a result, the type of the fingerprint pattern is determined to be of the arch pattern types α and β or the loop pattern types γ and δ.
In the case of the loop pattern type shown in FIG. 34(a), the core-type characteristic point is situated in the area surrounded by the horseshoe-shaped ridge lines al-ar and bl-br. In other words, a loop pattern is located in the vicinity of the core-type characteristic point. In contrast, in the tented arch pattern β shown in FIG. 34(b), the core-type characteristic point is surrounded by the arch lines al-ar, bl-br, and cl-cr.
Hence, a determination as to whether a fingerprint is to be classified as the loop pattern types γ and δ or as the tented arch pattern type β is made if extracted lines surrounding a core-type characteristic point assume an arch shape or a loop shape.
The majority of whorl patterns can be roughly classified into two types according to core-type characteristic points and orientation of ridge lines surrounding the core-type characteristic points. FIGS. 35(a) and 35(b) are illustrations for describing whorl patterns of these types. A fingerprint pattern shown in FIG. 35(a) has two core-type characteristic points, which are connected together by ridge and furrow lines. Further, annular ridge lines surround the core-type characteristic points. A fingerprint pattern shown in FIG. 35(b) also has two core-type characteristic points connected to whorl-shaped lines.
In a case where characteristic lines (characteristic lines) connected to the core-type characteristic points cannot be classified as either of the foregoing two pattern types, a detected characteristic point can be determined to be a characteristic point of a whorl pattern. Thus, a whorl pattern can be authenticated.
FIG. 36 is an illustration showing an example loop pattern. Two loop lines and two core-type characteristic points appear in the example. The loop pattern shown in FIG. 36 has two loop lines, and very few people have this type of fingerprint. The fingerprint of this pattern is determined by means of checking characteristic lines connected to the core-type characteristic points, thereby preventing false classification of the fingerprint of this type as the whorl pattern type.
In addition to the inventions described in Publicly-Known Publications 1 and 2, numerous techniques for correctly determining a pattern as precisely as possible from an input fingerprint image have hitherto been proposed.
However, when determination of pattern type of a fingerprint has failed, the person is not authenticated as a true person. More strict determination of pattern type is again required, thus involving a large amount of computation.
When the loop pattern shown in FIG. 36 is subjected to matching by use of the above-described determination method, the fingerprint having this loop pattern is subjected to fingerprint matching through strict determination. Hence, a failure of type determination is not allowed. If an input fingerprint has a narrow area, the pattern of the fingerprint cannot be determined accurately. In order to strictly determine the pattern type of a fingerprint, a wide fingerprint image of the fingerprint is required. Hence, if determination of pattern type of a fingerprint has failed during related-art personal authentication using fingerprint patterns, correct authentication of an individual becomes impossible.